Pandas Profiling Report

Dataset statistics

Number of variables	13
Number of observations	14116
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	1.4 MiB
Average record size in memory	104.0 B

Variable types

Numeric	8
Categorical	5

Alerts

`df_index` is highly correlated with `employee_id`	High correlation
`employee_id` is highly correlated with `df_index`	High correlation
`age` is highly correlated with `n_projects`	High correlation
`n_projects` is highly correlated with `age`	High correlation
`df_index` is highly correlated with `employee_id`	High correlation
`employee_id` is highly correlated with `df_index`	High correlation
`age` is highly correlated with `n_projects`	High correlation
`n_projects` is highly correlated with `age`	High correlation
`df_index` is highly correlated with `employee_id`	High correlation
`employee_id` is highly correlated with `df_index`	High correlation
`age` is highly correlated with `n_projects`	High correlation
`n_projects` is highly correlated with `age`	High correlation
`df_index` is highly correlated with `employee_id`	High correlation
`employee_id` is highly correlated with `df_index` and 1 other fields	High correlation
`age` is highly correlated with `marital_status` and 1 other fields	High correlation
`marital_status` is highly correlated with `age` and 1 other fields	High correlation
`avg_monthly_hrs` is highly correlated with `n_projects` and 2 other fields	High correlation
`n_projects` is highly correlated with `age` and 4 other fields	High correlation
`satisfaction` is highly correlated with `avg_monthly_hrs` and 2 other fields	High correlation
`status` is highly correlated with `employee_id` and 3 other fields	High correlation
`df_index` is uniformly distributed	Uniform
`df_index` has unique values	Unique
`employee_id` has unique values	Unique

Reproduction

Analysis started	2022-04-25 14:12:35.601132
Analysis finished	2022-04-25 14:13:02.900641
Duration	27.3 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

df_index
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	14116
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7071.104704

Minimum	0
Maximum	14144
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	110.4 KiB

Quantile statistics

Minimum	0
5-th percentile	705.75
Q1	3532.75
median	7070.5
Q3	10610.25
95-th percentile	13438.25
Maximum	14144
Range	14144
Interquartile range (IQR)	7077.5

Descriptive statistics

Standard deviation	4084.958507
Coefficient of variation (CV)	0.5776973582
Kurtosis	-1.200746217
Mean	7071.104704
Median Absolute Deviation (MAD)	3539
Skewness	0.0003525578936
Sum	99815714
Variance	16686886
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1	< 0.1%
9433	1	< 0.1%
9422	1	< 0.1%
9423	1	< 0.1%
9424	1	< 0.1%
9425	1	< 0.1%
9426	1	< 0.1%
9427	1	< 0.1%
9428	1	< 0.1%
9429	1	< 0.1%
Other values (14106)	14106	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
14144	1	< 0.1%
14143	1	< 0.1%
14142	1	< 0.1%
14141	1	< 0.1%
14140	1	< 0.1%
14139	1	< 0.1%
14138	1	< 0.1%
14137	1	< 0.1%
14136	1	< 0.1%
14135	1	< 0.1%

employee_id
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	14116
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	112120.6578

Minimum	100101
Maximum	148988
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	110.4 KiB

Quantile statistics

Minimum	100101
5-th percentile	101224.75
Q1	105773.5
median	111293.5
Q3	116655.25
95-th percentile	128001
Maximum	148988
Range	48887
Interquartile range (IQR)	10881.75

Descriptive statistics

Standard deviation	8497.639403
Coefficient of variation (CV)	0.07579013156
Kurtosis	2.759148176
Mean	112120.6578
Median Absolute Deviation (MAD)	5445.5
Skewness	1.304670041
Sum	1582695205
Variance	72209875.42
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
100101	1	< 0.1%
114863	1	< 0.1%
114846	1	< 0.1%
114847	1	< 0.1%
114849	1	< 0.1%
114851	1	< 0.1%
114852	1	< 0.1%
114853	1	< 0.1%
114855	1	< 0.1%
114856	1	< 0.1%
Other values (14106)	14106	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
100101	1	< 0.1%
100102	1	< 0.1%
100103	1	< 0.1%
100105	1	< 0.1%
100106	1	< 0.1%
100107	1	< 0.1%
100108	1	< 0.1%
100109	1	< 0.1%
100110	1	< 0.1%
100111	1	< 0.1%

Value	Count	Frequency (%)
148988	1	< 0.1%
148947	1	< 0.1%
148916	1	< 0.1%
148879	1	< 0.1%
148877	1	< 0.1%
148842	1	< 0.1%
148768	1	< 0.1%
148737	1	< 0.1%
148719	1	< 0.1%
148640	1	< 0.1%

age
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	36
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	32.89600453

Minimum	22
Maximum	57
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	110.4 KiB

Quantile statistics

Minimum	22
5-th percentile	22
Q1	24
median	29
Q3	41
95-th percentile	52
Maximum	57
Range	35
Interquartile range (IQR)	17

Descriptive statistics

Standard deviation	9.975000045
Coefficient of variation (CV)	0.3032283156
Kurtosis	-0.867621121
Mean	32.89600453
Median Absolute Deviation (MAD)	6
Skewness	0.7008830699
Sum	464360
Variance	99.50062591
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=36)

Value	Count	Frequency (%)
24	1308	9.3%
25	1246	8.8%
23	1196	8.5%
22	1166	8.3%
27	662	4.7%
29	660	4.7%
28	647	4.6%
26	626	4.4%
42	303	2.1%
37	284	2.0%
Other values (26)	6018	42.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
22	1166	8.3%
23	1196	8.5%
24	1308	9.3%
25	1246	8.8%
26	626	4.4%
27	662	4.7%
28	647	4.6%
29	660	4.7%
30	275	1.9%
31	225	1.6%

Value	Count	Frequency (%)
57	34	0.2%
56	22	0.2%
55	38	0.3%
54	226	1.6%
53	235	1.7%
52	252	1.8%
51	227	1.6%
50	233	1.7%
49	243	1.7%
48	272	1.9%

gender
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	110.4 KiB

Male	9287
Female	4829

Length

Max length	6
Median length	4
Mean length	4.684188155
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Male
2nd row	Female
3rd row	Male
4th row	Female
5th row	Male

Common Values

Value	Count	Frequency (%)
Male	9287	65.8%
Female	4829	34.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
male	9287	65.8%
female	4829	34.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

marital_status
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	110.4 KiB

Unmarried	7211
Married	6905

Length

Max length	9
Median length	9
Mean length	8.021677529
Min length	7

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Unmarried
2nd row	Unmarried
3rd row	Unmarried
4th row	Unmarried
5th row	Unmarried

Common Values

Value	Count	Frequency (%)
Unmarried	7211	51.1%
Married	6905	48.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
unmarried	7211	51.1%
married	6905	48.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

avg_monthly_hrs
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	249
Distinct (%)	1.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	199.9926325

Minimum	49
Maximum	310
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	110.4 KiB

Quantile statistics

Minimum	49
5-th percentile	128
Q1	155
median	199
Q3	245
95-th percentile	275
Maximum	310
Range	261
Interquartile range (IQR)	90

Descriptive statistics

Standard deviation	50.82695196
Coefficient of variation (CV)	0.2541441219
Kurtosis	-1.044324553
Mean	199.9926325
Median Absolute Deviation (MAD)	45
Skewness	0.01643063443
Sum	2823096
Variance	2583.379046
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
135	143	1.0%
156	141	1.0%
151	140	1.0%
149	139	1.0%
145	125	0.9%
143	124	0.9%
160	123	0.9%
260	118	0.8%
154	118	0.8%
148	118	0.8%
Other values (239)	12827	90.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
49	3	< 0.1%
52	1	< 0.1%
54	2	< 0.1%
55	1	< 0.1%
56	1	< 0.1%
60	1	< 0.1%
63	1	< 0.1%
65	1	< 0.1%
66	2	< 0.1%
67	4	< 0.1%

Value	Count	Frequency (%)
310	18	0.1%
309	15	0.1%
308	19	0.1%
307	14	0.1%
306	17	0.1%
305	18	0.1%
304	17	0.1%
303	6	< 0.1%
302	8	0.1%
301	21	0.1%

department
Categorical

Distinct	12
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	110.4 KiB

D00-SS	4601
D00-ENG	2573
D00-SP	2108
D00D00-IT	1152
D00-PD	853
Other values (7)	2829

Length

Max length	9
Median length	6
Mean length	6.427103995
Min length	6

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	D00-SS
2nd row	D00-MN
3rd row	D00-ENG
4th row	D00-MT
5th row	D00-ENG

Common Values

Value	Count	Frequency (%)
D00-SS	4601	32.6%
D00-ENG	2573	18.2%
D00-SP	2108	14.9%
D00D00-IT	1152	8.2%
D00-PD	853	6.0%
D00-MT	812	5.8%
D00-FN	722	5.1%
D00-MN	590	4.2%
D00-IT	207	1.5%
D00-AD	175	1.2%
Other values (2)	323	2.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
d00-ss	4601	32.6%
d00-eng	2573	18.2%
d00-sp	2108	14.9%
d00d00-it	1152	8.2%
d00-pd	853	6.0%
d00-mt	812	5.8%
d00-fn	722	5.1%
d00-mn	590	4.2%
d00-it	207	1.5%
d00-ad	175	1.2%
Other values (2)	323	2.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

last_evaluation
Real number (ℝ_≥0)

Distinct	12185
Distinct (%)	86.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.7183221625

Minimum	0.316175
Maximum	1
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	110.4 KiB

Quantile statistics

Minimum	0.316175
5-th percentile	0.45900175
Q1	0.5795165
median	0.7183221625
Q3	0.85685375
95-th percentile	0.976118
Maximum	1
Range	0.683825
Interquartile range (IQR)	0.27733725

Descriptive statistics

Standard deviation	0.1636994965
Coefficient of variation (CV)	0.2278914741
Kurtosis	-0.9861755436
Mean	0.7183221625
Median Absolute Deviation (MAD)	0.138693
Skewness	-0.06847563778
Sum	10139.83565
Variance	0.02679752515
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.7183221625	1487	10.5%
1	356	2.5%
0.896246	3	< 0.1%
0.66631	2	< 0.1%
0.838646	2	< 0.1%
0.974814	2	< 0.1%
0.889985	2	< 0.1%
0.744834	2	< 0.1%
0.955579	2	< 0.1%
0.574166	2	< 0.1%
Other values (12175)	12256	86.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.316175	1	< 0.1%
0.317279	1	< 0.1%
0.320953	1	< 0.1%
0.322828	1	< 0.1%
0.324239	1	< 0.1%
0.325885	1	< 0.1%
0.328417	1	< 0.1%
0.329813	1	< 0.1%
0.33132	1	< 0.1%
0.331545	1	< 0.1%

Value	Count	Frequency (%)
1	356	2.5%
0.999808	1	< 0.1%
0.99939	1	< 0.1%
0.999365	1	< 0.1%
0.999259	1	< 0.1%
0.99921	1	< 0.1%
0.99915	1	< 0.1%
0.999145	1	< 0.1%
0.999113	1	< 0.1%
0.999062	1	< 0.1%

n_projects
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.777769906

Minimum	1
Maximum	7
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	110.4 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	3
median	4
Q3	5
95-th percentile	6
Maximum	7
Range	6
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.249693245
Coefficient of variation (CV)	0.3308018422
Kurtosis	-0.4814501348
Mean	3.777769906
Median Absolute Deviation (MAD)	1
Skewness	0.3152883573
Sum	53327
Variance	1.561733206
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
4	4044	28.6%
3	3788	26.8%
5	2566	18.2%
2	2322	16.4%
6	1093	7.7%
7	242	1.7%
1	61	0.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	61	0.4%
2	2322	16.4%
3	3788	26.8%
4	4044	28.6%
5	2566	18.2%
6	1093	7.7%
7	242	1.7%

Value	Count	Frequency (%)
7	242	1.7%
6	1093	7.7%
5	2566	18.2%
4	4044	28.6%
3	3788	26.8%
2	2322	16.4%
1	61	0.4%

salary
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	110.4 KiB

low	6889
medium	6086
high	1141

Length

Max length	6
Median length	4
Mean length	4.374256163
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	low
2nd row	high
3rd row	low
4th row	low
5th row	low

Common Values

Value	Count	Frequency (%)
low	6889	48.8%
medium	6086	43.1%
high	1141	8.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
low	6889	48.8%
medium	6086	43.1%
high	1141	8.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

satisfaction
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	13493
Distinct (%)	95.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.6216535485

Minimum	0.0400584
Maximum	1
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	110.4 KiB

Quantile statistics

Minimum	0.0400584
5-th percentile	0.13733525
Q1	0.452826
median	0.6525485
Q3	0.82296025
95-th percentile	0.969316
Maximum	1
Range	0.9599416
Interquartile range (IQR)	0.37013425

Descriptive statistics

Standard deviation	0.2491466421
Coefficient of variation (CV)	0.4007805355
Kurtosis	-0.6424061277
Mean	0.6216535485
Median Absolute Deviation (MAD)	0.1837245
Skewness	-0.481363745
Sum	8775.261491
Variance	0.06207404925
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	356	2.5%
0.6525485	150	1.1%
0.882892	2	< 0.1%
0.414375	2	< 0.1%
0.570954	2	< 0.1%
0.697019	2	< 0.1%
0.922457	2	< 0.1%
0.497612	2	< 0.1%
0.470955	2	< 0.1%
0.565165	2	< 0.1%
Other values (13483)	13594	96.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.0400584	1	< 0.1%
0.0401908	1	< 0.1%
0.0404774	1	< 0.1%
0.0413017	1	< 0.1%
0.0424075	1	< 0.1%
0.0448441	1	< 0.1%
0.0455807	1	< 0.1%
0.0460936	1	< 0.1%
0.0494592	1	< 0.1%
0.0495488	1	< 0.1%

Value	Count	Frequency (%)
1	356	2.5%
0.99988	1	< 0.1%
0.999763	1	< 0.1%
0.999704	1	< 0.1%
0.999593	1	< 0.1%
0.999586	1	< 0.1%
0.999556	1	< 0.1%
0.999512	1	< 0.1%
0.999439	1	< 0.1%
0.999355	1	< 0.1%

tenure
Real number (ℝ_≥0)

Distinct	8
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.492419949

Minimum	2
Maximum	10
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	110.4 KiB

Quantile statistics

Minimum	2
5-th percentile	2
Q1	3
median	3
Q3	4
95-th percentile	6
Maximum	10
Range	8
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.453547798
Coefficient of variation (CV)	0.4162007487
Kurtosis	4.857579404
Mean	3.492419949
Median Absolute Deviation (MAD)	1
Skewness	1.871919281
Sum	49299
Variance	2.1128012
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
3	6156	43.6%
2	3019	21.4%
4	2386	16.9%
5	1363	9.7%
6	659	4.7%
10	198	1.4%
7	180	1.3%
8	155	1.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	3019	21.4%
3	6156	43.6%
4	2386	16.9%
5	1363	9.7%
6	659	4.7%
7	180	1.3%
8	155	1.1%
10	198	1.4%

Value	Count	Frequency (%)
10	198	1.4%
8	155	1.1%
7	180	1.3%
6	659	4.7%
5	1363	9.7%
4	2386	16.9%
3	6156	43.6%
2	3019	21.4%

status
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	110.4 KiB

Employed	10761
Left	3355

Length

Max length	8
Median length	8
Mean length	7.049305752
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Employed
2nd row	Employed
3rd row	Employed
4th row	Employed
5th row	Left

Common Values

Value	Count	Frequency (%)
Employed	10761	76.2%
Left	3355	23.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
employed	10761	76.2%
left	3355	23.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	df_index	employee_id	age	gender	marital_status	avg_monthly_hrs	department	last_evaluation	n_projects	salary	satisfaction	tenure	status
0	0	100101	26	Male	Unmarried	156.0	D00-SS	0.599109	2	low	0.565100	2.0	Employed
1	1	100102	25	Female	Unmarried	172.0	D00-MN	0.754200	3	high	0.486220	10.0	Employed
2	2	100103	24	Male	Unmarried	268.0	D00-ENG	0.682366	3	low	0.612525	2.0	Employed
3	3	100105	23	Female	Unmarried	192.0	D00-MT	0.759711	3	low	0.615641	3.0	Employed
4	4	100106	29	Male	Unmarried	145.0	D00-ENG	0.517110	2	low	0.517684	3.0	Left
5	5	100107	52	Male	Married	178.0	D00-ENG	0.500988	6	low	0.365291	2.0	Employed
6	6	100108	24	Male	Unmarried	184.0	D00-ENG	0.815477	3	medium	0.924365	3.0	Employed
7	7	100109	24	Male	Unmarried	177.0	D00-MT	0.461489	3	high	0.350168	3.0	Employed
8	8	100110	25	Male	Unmarried	235.0	D00-ENG	0.946399	3	medium	0.608787	2.0	Employed
9	9	100111	22	Male	Unmarried	138.0	D00-ENG	0.489286	2	low	0.369778	3.0	Left

Last rows

	df_index	employee_id	age	gender	marital_status	avg_monthly_hrs	department	last_evaluation	n_projects	salary	satisfaction	tenure	status
14106	14135	148640	33	Female	Married	218.0	D00-PD	0.536230	3	low	0.754514	3.0	Employed
14107	14136	148719	28	Male	Unmarried	177.0	D00-ENG	1.000000	3	medium	0.812509	2.0	Employed
14108	14137	148737	31	Female	Married	162.0	D00-PR	0.565725	3	low	0.851234	2.0	Employed
14109	14138	148768	43	Male	Married	232.0	D00-FN	0.927203	5	medium	0.902979	5.0	Left
14110	14139	148842	42	Male	Married	232.0	D00-SS	0.436913	5	medium	0.664634	4.0	Employed
14111	14140	148877	25	Male	Unmarried	136.0	D00-SS	0.692963	3	high	0.792814	2.0	Employed
14112	14141	148879	26	Male	Unmarried	217.0	D00-MT	0.718322	3	high	0.765757	3.0	Employed
14113	14142	148916	23	Female	Unmarried	171.0	D00-ENG	0.718322	2	low	0.583852	2.0	Employed
14114	14143	148947	28	Male	Unmarried	221.0	D00-SP	0.840325	3	medium	0.795188	2.0	Employed
14115	14144	148988	22	Male	Unmarried	130.0	D00-SP	0.513891	2	medium	0.406645	3.0	Left

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Phik (φk)

Missing values

Sample

First rows

Last rows